Overview

Brought to you by YData

Dataset statistics

Number of variables12
Number of observations248
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory23.4 KiB
Average record size in memory96.5 B

Variable types

Categorical2
DateTime1
Numeric9

Alerts

10_MA is highly overall correlated with 20_MA and 8 other fieldsHigh correlation
20_MA is highly overall correlated with 10_MA and 8 other fieldsHigh correlation
Adj Close is highly overall correlated with 10_MA and 8 other fieldsHigh correlation
Close is highly overall correlated with 10_MA and 8 other fieldsHigh correlation
High is highly overall correlated with 10_MA and 8 other fieldsHigh correlation
Low is highly overall correlated with 10_MA and 8 other fieldsHigh correlation
Open is highly overall correlated with 10_MA and 8 other fieldsHigh correlation
Ticker is highly overall correlated with 10_MA and 8 other fieldsHigh correlation
Ticker_Encoded is highly overall correlated with 10_MA and 8 other fieldsHigh correlation
Volume is highly overall correlated with 10_MA and 8 other fieldsHigh correlation
Ticker is uniformly distributed Uniform
Ticker_Encoded is uniformly distributed Uniform
High has unique values Unique
Low has unique values Unique
Volume has unique values Unique
10_MA has unique values Unique
20_MA has unique values Unique
Volatility has 8 (3.2%) zeros Zeros

Reproduction

Analysis started2025-03-29 16:42:52.716214
Analysis finished2025-03-29 16:43:06.658492
Duration13.94 seconds
Software versionydata-profiling vv4.16.0
Download configurationconfig.json

Variables

Ticker
Categorical

High correlation  Uniform 

Distinct4
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
AAPL
62 
MSFT
62 
NFLX
62 
GOOG
62 

Length

Max length4
Median length4
Mean length4
Min length4

Characters and Unicode

Total characters992
Distinct characters11
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowAAPL
2nd rowAAPL
3rd rowAAPL
4th rowAAPL
5th rowAAPL

Common Values

ValueCountFrequency (%)
AAPL 62
25.0%
MSFT 62
25.0%
NFLX 62
25.0%
GOOG 62
25.0%

Length

2025-03-29T22:13:06.799653image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-03-29T22:13:06.960681image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
aapl 62
25.0%
msft 62
25.0%
nflx 62
25.0%
goog 62
25.0%

Most occurring characters

ValueCountFrequency (%)
A 124
12.5%
L 124
12.5%
F 124
12.5%
G 124
12.5%
O 124
12.5%
P 62
6.2%
M 62
6.2%
T 62
6.2%
S 62
6.2%
X 62
6.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 992
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
A 124
12.5%
L 124
12.5%
F 124
12.5%
G 124
12.5%
O 124
12.5%
P 62
6.2%
M 62
6.2%
T 62
6.2%
S 62
6.2%
X 62
6.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 992
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
A 124
12.5%
L 124
12.5%
F 124
12.5%
G 124
12.5%
O 124
12.5%
P 62
6.2%
M 62
6.2%
T 62
6.2%
S 62
6.2%
X 62
6.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 992
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
A 124
12.5%
L 124
12.5%
F 124
12.5%
G 124
12.5%
O 124
12.5%
P 62
6.2%
M 62
6.2%
T 62
6.2%
S 62
6.2%
X 62
6.2%

Date
Date

Distinct62
Distinct (%)25.0%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
Minimum2023-02-07 00:00:00
Maximum2023-05-05 00:00:00
Invalid dates0
Invalid dates (%)0.0%
2025-03-29T22:13:07.159917image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-29T22:13:07.401879image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

Open
Real number (ℝ)

High correlation 

Distinct244
Distinct (%)98.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean215.25209
Minimum89.540001
Maximum372.41
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.1 KiB
2025-03-29T22:13:07.642490image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum89.540001
5-th percentile93.827001
Q1135.235
median208.765
Q3304.17751
95-th percentile342.9085
Maximum372.41
Range282.87
Interquartile range (IQR)168.9425

Descriptive statistics

Standard deviation91.691315
Coefficient of variation (CV)0.42597177
Kurtosis-1.5939339
Mean215.25209
Median Absolute Deviation (MAD)95.580002
Skewness0.02880724
Sum53382.519
Variance8407.2972
MonotonicityNot monotonic
2025-03-29T22:13:07.868942image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
165.1900024 2
 
0.8%
105.3199997 2
 
0.8%
107.3899994 2
 
0.8%
295.9700012 2
 
0.8%
150.9499969 1
 
0.4%
152.1199951 1
 
0.4%
153.1100006 1
 
0.4%
153.5099945 1
 
0.4%
152.3500061 1
 
0.4%
150.1999969 1
 
0.4%
Other values (234) 234
94.4%
ValueCountFrequency (%)
89.54000092 1
0.4%
89.62999725 1
0.4%
89.86000061 1
0.4%
90.08999634 1
0.4%
90.16000366 1
0.4%
90.56500244 1
0.4%
91.93399811 1
0.4%
92.12999725 1
0.4%
92.5 1
0.4%
92.73999786 1
0.4%
ValueCountFrequency (%)
372.4100037 1
0.4%
360.019989 1
0.4%
359.1600037 1
0.4%
358.5100098 1
0.4%
357.5499878 1
0.4%
356.6300049 1
0.4%
355 1
0.4%
349.5 1
0.4%
348.4899902 1
0.4%
347.9100037 1
0.4%

High
Real number (ℝ)

High correlation  Unique 

Distinct248
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean217.91966
Minimum90.129997
Maximum373.82999
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.1 KiB
2025-03-29T22:13:08.117778image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum90.129997
5-th percentile95.236251
Q1137.44
median212.615
Q3307.565
95-th percentile346.22349
Maximum373.82999
Range283.69999
Interquartile range (IQR)170.125

Descriptive statistics

Standard deviation92.863023
Coefficient of variation (CV)0.42613421
Kurtosis-1.5956665
Mean217.91966
Median Absolute Deviation (MAD)95.015007
Skewness0.032416937
Sum54044.076
Variance8623.541
MonotonicityNot monotonic
2025-03-29T22:13:08.358909image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
155.2299957 1
 
0.4%
154.5800018 1
 
0.4%
154.3300018 1
 
0.4%
151.3399963 1
 
0.4%
154.2599945 1
 
0.4%
153.7700043 1
 
0.4%
155.5 1
 
0.4%
156.3300018 1
 
0.4%
153 1
 
0.4%
151.3000031 1
 
0.4%
Other values (238) 238
96.0%
ValueCountFrequency (%)
90.12999725 1
0.4%
90.44999695 1
0.4%
91.19999695 1
0.4%
91.44999695 1
0.4%
92.12999725 1
0.4%
92.36000061 1
0.4%
92.48000336 1
0.4%
93.08000183 1
0.4%
93.18000031 1
0.4%
93.41500092 1
0.4%
ValueCountFrequency (%)
373.8299866 1
0.4%
368.1900024 1
0.4%
364.1799927 1
0.4%
363.75 1
0.4%
362.8800049 1
0.4%
362.1400146 1
0.4%
361.5 1
0.4%
359.7000122 1
0.4%
349.7999878 1
0.4%
349 1
0.4%

Low
Real number (ℝ)

High correlation  Unique 

Distinct248
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean212.69745
Minimum88.860001
Maximum361.73999
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.1 KiB
2025-03-29T22:13:08.590055image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum88.860001
5-th percentile92.702002
Q1134.82249
median208.185
Q3295.4375
95-th percentile337.48601
Maximum361.73999
Range272.87999
Interquartile range (IQR)160.61501

Descriptive statistics

Standard deviation90.147881
Coefficient of variation (CV)0.4238315
Kurtosis-1.5956436
Mean212.69745
Median Absolute Deviation (MAD)87.440002
Skewness0.017889058
Sum52748.968
Variance8126.6404
MonotonicityNot monotonic
2025-03-29T22:13:09.052806image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
150.6399994 1
 
0.4%
151.1699982 1
 
0.4%
150.4199982 1
 
0.4%
149.2200012 1
 
0.4%
150.9199982 1
 
0.4%
150.8600006 1
 
0.4%
152.8800049 1
 
0.4%
153.3500061 1
 
0.4%
150.8500061 1
 
0.4%
148.4100037 1
 
0.4%
Other values (238) 238
96.0%
ValueCountFrequency (%)
88.86000061 1
0.4%
89.51999664 1
0.4%
89.61000061 1
0.4%
89.76999664 1
0.4%
89.84999847 1
0.4%
89.94000244 1
0.4%
90.01000214 1
0.4%
90.80000305 1
0.4%
90.87000275 1
0.4%
92 1
0.4%
ValueCountFrequency (%)
361.7399902 1
0.4%
358.3099976 1
0.4%
354.2399902 1
0.4%
354.1799927 1
0.4%
353.3999939 1
0.4%
350.3099976 1
0.4%
347.1400146 1
0.4%
344.25 1
0.4%
343.9500122 1
0.4%
342.4400024 1
0.4%

Close
Real number (ℝ)

High correlation 

Distinct244
Distinct (%)98.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean215.38167
Minimum89.349998
Maximum366.82999
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.1 KiB
2025-03-29T22:13:09.291318image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum89.349998
5-th percentile94.197999
Q1136.3475
median209.92001
Q3303.9425
95-th percentile344.38451
Maximum366.82999
Range277.47999
Interquartile range (IQR)167.59501

Descriptive statistics

Standard deviation91.461989
Coefficient of variation (CV)0.42465075
Kurtosis-1.5933559
Mean215.38167
Median Absolute Deviation (MAD)94.174995
Skewness0.025335188
Sum53414.655
Variance8365.2955
MonotonicityNot monotonic
2025-03-29T22:13:09.521473image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
163.7599945 2
 
0.8%
106.1200027 2
 
0.8%
105.1200027 2
 
0.8%
305.4100037 2
 
0.8%
153.8500061 1
 
0.4%
153.1999969 1
 
0.4%
155.3300018 1
 
0.4%
153.7100067 1
 
0.4%
152.5500031 1
 
0.4%
148.4799957 1
 
0.4%
Other values (234) 234
94.4%
ValueCountFrequency (%)
89.34999847 1
0.4%
90.09999847 1
0.4%
90.30000305 1
0.4%
90.51000214 1
0.4%
91.01000214 1
0.4%
91.06999969 1
0.4%
91.66000366 1
0.4%
91.80000305 1
0.4%
92.05000305 1
0.4%
92.30999756 1
0.4%
ValueCountFrequency (%)
366.8299866 1
0.4%
362.9500122 1
0.4%
362.5 1
0.4%
361.4200134 1
0.4%
359.9599915 1
0.4%
358.5700073 1
0.4%
350.7099915 1
0.4%
348.2799988 1
0.4%
347.9599915 1
0.4%
347.3599854 1
0.4%

Adj Close
Real number (ℝ)

High correlation 

Distinct244
Distinct (%)98.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean215.3627
Minimum89.349998
Maximum366.82999
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.1 KiB
2025-03-29T22:13:09.747346image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum89.349998
5-th percentile94.197999
Q1136.3475
median209.92001
Q3303.9425
95-th percentile344.38451
Maximum366.82999
Range277.47999
Interquartile range (IQR)167.59501

Descriptive statistics

Standard deviation91.45475
Coefficient of variation (CV)0.42465455
Kurtosis-1.5929694
Mean215.3627
Median Absolute Deviation (MAD)94.174995
Skewness0.025751826
Sum53409.949
Variance8363.9713
MonotonicityNot monotonic
2025-03-29T22:13:09.978589image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
163.7599945 2
 
0.8%
106.1200027 2
 
0.8%
105.1200027 2
 
0.8%
305.4100037 2
 
0.8%
153.8500061 1
 
0.4%
153.1999969 1
 
0.4%
155.3300018 1
 
0.4%
153.7100067 1
 
0.4%
152.5500031 1
 
0.4%
148.4799957 1
 
0.4%
Other values (234) 234
94.4%
ValueCountFrequency (%)
89.34999847 1
0.4%
90.09999847 1
0.4%
90.30000305 1
0.4%
90.51000214 1
0.4%
91.01000214 1
0.4%
91.06999969 1
0.4%
91.66000366 1
0.4%
91.80000305 1
0.4%
92.05000305 1
0.4%
92.30999756 1
0.4%
ValueCountFrequency (%)
366.8299866 1
0.4%
362.9500122 1
0.4%
362.5 1
0.4%
361.4200134 1
0.4%
359.9599915 1
0.4%
358.5700073 1
0.4%
350.7099915 1
0.4%
348.2799988 1
0.4%
347.9599915 1
0.4%
347.3599854 1
0.4%

Volume
Real number (ℝ)

High correlation  Unique 

Distinct248
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean32082104
Minimum2657900
Maximum1.133164 × 108
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.1 KiB
2025-03-29T22:13:10.210274image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum2657900
5-th percentile4460075
Q117141800
median27340000
Q347717725
95-th percentile73676825
Maximum1.133164 × 108
Range1.106585 × 108
Interquartile range (IQR)30575925

Descriptive statistics

Standard deviation22335899
Coefficient of variation (CV)0.69621053
Kurtosis0.2479315
Mean32082104
Median Absolute Deviation (MAD)18542200
Skewness0.77594711
Sum7.9563618 × 109
Variance4.9889237 × 1014
MonotonicityNot monotonic
2025-03-29T22:13:10.485064image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
83322600 1
 
0.4%
64120100 1
 
0.4%
56007100 1
 
0.4%
57450700 1
 
0.4%
62199000 1
 
0.4%
61707600 1
 
0.4%
65573800 1
 
0.4%
68167900 1
 
0.4%
59144100 1
 
0.4%
58867200 1
 
0.4%
Other values (238) 238
96.0%
ValueCountFrequency (%)
2657900 1
0.4%
3298100 1
0.4%
3479500 1
0.4%
3676100 1
0.4%
3879700 1
0.4%
3965400 1
0.4%
3966000 1
0.4%
3988600 1
0.4%
4044800 1
0.4%
4205500 1
0.4%
ValueCountFrequency (%)
113316400 1
0.4%
98944600 1
0.4%
97798600 1
0.4%
87558000 1
0.4%
84457100 1
0.4%
83322600 1
0.4%
81235400 1
0.4%
77167900 1
0.4%
76161100 1
0.4%
76140300 1
0.4%

Ticker_Encoded
Categorical

High correlation  Uniform 

Distinct4
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
0
62 
2
62 
3
62 
1
62 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters248
Distinct characters4
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 62
25.0%
2 62
25.0%
3 62
25.0%
1 62
25.0%

Length

2025-03-29T22:13:10.707468image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-03-29T22:13:10.845235image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 62
25.0%
2 62
25.0%
3 62
25.0%
1 62
25.0%

Most occurring characters

ValueCountFrequency (%)
0 62
25.0%
2 62
25.0%
3 62
25.0%
1 62
25.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 248
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 62
25.0%
2 62
25.0%
3 62
25.0%
1 62
25.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 248
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 62
25.0%
2 62
25.0%
3 62
25.0%
1 62
25.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 248
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 62
25.0%
2 62
25.0%
3 62
25.0%
1 62
25.0%

10_MA
Real number (ℝ)

High correlation  Unique 

Distinct248
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean215.03685
Minimum91.61
Maximum364.89
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.1 KiB
2025-03-29T22:13:11.030942image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum91.61
5-th percentile93.66585
Q1138.28225
median209.659
Q3299.735
95-th percentile343.0788
Maximum364.89
Range273.28
Interquartile range (IQR)161.45275

Descriptive statistics

Standard deviation92.014238
Coefficient of variation (CV)0.42789985
Kurtosis-1.5736758
Mean215.03685
Median Absolute Deviation (MAD)90.203002
Skewness0.050646878
Sum53329.139
Variance8466.62
MonotonicityNot monotonic
2025-03-29T22:13:11.282077image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
154.6499939 1
 
0.4%
153.284996 1
 
0.4%
152.4799957 1
 
0.4%
152.1124954 1
 
0.4%
152.4599976 1
 
0.4%
152.5833308 1
 
0.4%
152.9757124 1
 
0.4%
153.0674992 1
 
0.4%
153.0099996 1
 
0.4%
152.5569992 1
 
0.4%
Other values (238) 238
96.0%
ValueCountFrequency (%)
91.60999985 1
0.4%
91.7090004 1
0.4%
91.78600006 1
0.4%
91.92099991 1
0.4%
92.20599976 1
0.4%
92.26500015 1
0.4%
92.36500015 1
0.4%
92.53100052 1
0.4%
92.68700104 1
0.4%
92.70899963 1
0.4%
ValueCountFrequency (%)
364.8899994 1
0.4%
364.0933329 1
0.4%
362.9500122 1
0.4%
359.941428 1
0.4%
359.909996 1
0.4%
359.6949972 1
0.4%
359.6419983 1
0.4%
358.7874985 1
0.4%
357.5844421 1
0.4%
355.5759979 1
0.4%

20_MA
Real number (ℝ)

High correlation  Unique 

Distinct248
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean214.5584
Minimum92.8955
Maximum364.89
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.1 KiB
2025-03-29T22:13:11.527374image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum92.8955
5-th percentile94.387276
Q1139.73913
median210.408
Q3296.90562
95-th percentile347.93375
Maximum364.89
Range271.9945
Interquartile range (IQR)157.1665

Descriptive statistics

Standard deviation92.594142
Coefficient of variation (CV)0.43155683
Kurtosis-1.5674346
Mean214.5584
Median Absolute Deviation (MAD)90.140251
Skewness0.065778001
Sum53210.483
Variance8573.6752
MonotonicityNot monotonic
2025-03-29T22:13:11.785741image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
154.6499939 1
 
0.4%
153.284996 1
 
0.4%
152.4799957 1
 
0.4%
152.1124954 1
 
0.4%
152.4599976 1
 
0.4%
152.5833308 1
 
0.4%
152.9757124 1
 
0.4%
153.0674992 1
 
0.4%
153.0099996 1
 
0.4%
152.5569992 1
 
0.4%
Other values (238) 238
96.0%
ValueCountFrequency (%)
92.89550018 1
0.4%
92.93300018 1
0.4%
92.97550049 1
0.4%
93.09300003 1
0.4%
93.17400055 1
0.4%
93.31549988 1
0.4%
93.50800056 1
0.4%
93.68249969 1
0.4%
93.87500076 1
0.4%
94.29388852 1
0.4%
ValueCountFrequency (%)
364.8899994 1
0.4%
364.0933329 1
0.4%
362.9500122 1
0.4%
359.941428 1
0.4%
359.909996 1
0.4%
359.6949972 1
0.4%
359.6419983 1
0.4%
358.7874985 1
0.4%
357.5844421 1
0.4%
355.5759979 1
0.4%

Volatility
Real number (ℝ)

Zeros 

Distinct241
Distinct (%)97.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.017454439
Minimum0
Maximum0.035783703
Zeros8
Zeros (%)3.2%
Negative0
Negative (%)0.0%
Memory size2.1 KiB
2025-03-29T22:13:12.044795image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.0097572299
Q10.013545625
median0.016278642
Q30.020507019
95-th percentile0.033192498
Maximum0.035783703
Range0.035783703
Interquartile range (IQR)0.0069613943

Descriptive statistics

Standard deviation0.0068412886
Coefficient of variation (CV)0.39195121
Kurtosis1.271094
Mean0.017454439
Median Absolute Deviation (MAD)0.0034058668
Skewness0.46063987
Sum4.328701
Variance4.680323 × 10-5
MonotonicityNot monotonic
2025-03-29T22:13:12.298017image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 8
 
3.2%
0.007595164624 1
 
0.4%
0.00932802808 1
 
0.4%
0.01536352333 1
 
0.4%
0.01337346342 1
 
0.4%
0.01357336779 1
 
0.4%
0.01309849429 1
 
0.4%
0.01235940654 1
 
0.4%
0.0142590829 1
 
0.4%
0.01364137258 1
 
0.4%
Other values (231) 231
93.1%
ValueCountFrequency (%)
0 8
3.2%
0.005297080641 1
 
0.4%
0.006051230363 1
 
0.4%
0.007595164624 1
 
0.4%
0.009149032935 1
 
0.4%
0.00932802808 1
 
0.4%
0.01055431912 1
 
0.4%
0.01061491659 1
 
0.4%
0.01067579195 1
 
0.4%
0.0108311671 1
 
0.4%
ValueCountFrequency (%)
0.03578370319 1
0.4%
0.03539201426 1
0.4%
0.03536232101 1
0.4%
0.03515820335 1
0.4%
0.03514646026 1
0.4%
0.03510090883 1
0.4%
0.03455015309 1
0.4%
0.03437028819 1
0.4%
0.03419026442 1
0.4%
0.0337778518 1
0.4%

Interactions

2025-03-29T22:13:04.550101image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
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2025-03-29T22:13:00.219448image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
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2025-03-29T22:12:58.713662image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-29T22:13:00.038577image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-29T22:13:01.417860image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-29T22:13:02.825890image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-29T22:13:04.362041image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Correlations

2025-03-29T22:13:12.505176image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
10_MA20_MAAdj CloseCloseHighLowOpenTickerTicker_EncodedVolatilityVolume
10_MA1.0000.9940.9900.9900.9910.9910.9910.9530.9530.163-0.577
20_MA0.9941.0000.9790.9790.9800.9800.9810.9680.9680.143-0.580
Adj Close0.9900.9791.0001.0000.9990.9980.9960.9510.9510.187-0.566
Close0.9900.9791.0001.0000.9990.9980.9960.9510.9510.187-0.566
High0.9910.9800.9990.9991.0000.9980.9980.9500.9500.183-0.564
Low0.9910.9800.9980.9980.9981.0000.9980.9440.9440.186-0.573
Open0.9910.9810.9960.9960.9980.9981.0000.9520.9520.182-0.574
Ticker0.9530.9680.9510.9510.9500.9440.9521.0001.0000.4110.719
Ticker_Encoded0.9530.9680.9510.9510.9500.9440.9521.0001.0000.4110.719
Volatility0.1630.1430.1870.1870.1830.1860.1820.4110.4111.000-0.414
Volume-0.577-0.580-0.566-0.566-0.564-0.573-0.5740.7190.719-0.4141.000

Missing values

2025-03-29T22:13:06.274816image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
A simple visualization of nullity by column.
2025-03-29T22:13:06.511169image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

TickerDateOpenHighLowCloseAdj CloseVolumeTicker_Encoded10_MA20_MAVolatility
0AAPL2023-02-07150.639999155.229996150.639999154.649994154.414230833226000154.649994154.6499940.000000
1AAPL2023-02-08153.880005154.580002151.169998151.919998151.688400641201000153.284996153.2849960.000000
2AAPL2023-02-09153.779999154.330002150.419998150.869995150.639999560071000152.479996152.4799960.007595
3AAPL2023-02-10149.460007151.339996149.220001151.009995151.009995574507000152.112495152.1124950.009328
4AAPL2023-02-13150.949997154.259995150.919998153.850006153.850006621990000152.459998152.4599980.015364
5AAPL2023-02-14152.119995153.770004150.860001153.199997153.199997617076000152.583331152.5833310.013373
6AAPL2023-02-15153.110001155.500000152.880005155.330002155.330002655738000152.975712152.9757120.013573
7AAPL2023-02-16153.509995156.330002153.350006153.710007153.710007681679000153.067499153.0674990.013098
8AAPL2023-02-17152.350006153.000000150.850006152.550003152.550003591441000153.010000153.0100000.012359
9AAPL2023-02-21150.199997151.300003148.410004148.479996148.479996588672000152.556999152.5569990.014259
TickerDateOpenHighLowCloseAdj CloseVolumeTicker_Encoded10_MA20_MAVolatility
238GOOG2023-04-24106.050003107.320000105.360001106.779999106.779999214109001106.414001105.3305000.015369
239GOOG2023-04-25106.610001107.440002104.559998104.610001104.610001314081001106.263000105.4080010.016538
240GOOG2023-04-26105.559998107.019997103.269997104.449997104.449997370682001106.186000105.5625000.016348
241GOOG2023-04-27105.230003109.150002104.419998108.370003108.370003382352001106.204000105.8860000.018317
242GOOG2023-04-28107.800003108.290001106.040001108.220001108.220001239579001106.080000106.2310010.017873
243GOOG2023-05-01107.720001108.680000107.500000107.709999107.709999209263001106.209000106.4165000.015343
244GOOG2023-05-02107.660004107.730003104.500000105.980003105.980003203431001106.295000106.4700000.015762
245GOOG2023-05-03106.220001108.129997105.620003106.120003106.120003171163001106.405001106.5200000.015748
246GOOG2023-05-04106.160004106.300003104.699997105.209999105.209999197806001106.336001106.5330010.015796
247GOOG2023-05-05105.320000106.440002104.738998106.214996106.214996207053001106.366500106.3987500.016119